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최신 SAP Certified Associate C_BCSBS_2502 무료샘플문제 (Q29-Q34):

질문 # 29
Which SAP Business Suite component is primarily used for customer relationship management? Please choose the correct answer.

A. SAP Business Warehouse
B. SAP S/4HANA
C. SAP SuccessFactors
D. SAP CRM

정답：D

질문 # 30
What are some scenarios that SAP Business Data Cloud supports?
Note: There are 3 correct answers to this question.

A. Training large language models
B. Advanced data modeling and data warehousing
C. Machine learning and artificial intelligence
D. Out-of-the-box reporting
E. Risk management reporting

정답：B,C,D

설명：
The question asks for scenarios supported bySAP Business Data Cloud, a Software-as-a-Service (SaaS) solution that integrates data management, analytics, and AI capabilities to meet the needs of modern organizations. According to official SAP documentation,SAP Business Data Cloudsupports a range of scenarios, including machine learning and artificial intelligence, advanced data modeling and data warehousing, and out-of-the-box reporting. These align with Options C, D, and E, making them the correct answers.
Explanation of Correct Answers:
Option C: Machine learning and artificial intelligence
This is correct becauseSAP Business Data Cloudexplicitly supports machine learning (ML) and artificial intelligence (AI) scenarios, particularly through its integration withSAP Databricks. This component provides data scientists with tools to develop and deploy AI/ML models using harmonized SAP and third-party data.
TheDescribing SAP Business Data Cloudlesson on learning.sap.com states:
"SAP Business Data Cloud can handle many use-cases including: Support the development of AI and machine learning models. ... SAP Databricks - to provide the data scientist with artificial intelligence (AI) / machine learning (ML) development tools." learning.sap.com Additionally, the documentation highlights:
"What makes SAP Business Data Cloud so powerful, is that it offers the tools and technologies to meet all data and analytics requirements of a modern and agile organization. It uses the latest technology to support scenarios such as: ... Machine learning and artificial intelligence." learning.sap.com This confirms thatSAP Business Data Cloudsupports AI/ML scenarios, such as predictive analytics, anomaly detection, and advanced automation, by leveragingSAP DatabricksandSAP Business Technology Platform (BTP)for scalable model development and deployment.
Option D: Advanced data modeling and data warehousing
This is correct becauseSAP Business Data Cloudprovides robust capabilities for advanced data modeling and data warehousing, primarily throughSAP Datasphere, which serves as the foundational data management layer. The documentation states:
"SAP Business Data Cloud provides data warehousing features including a manual data integration and data modeling approach, AI and machine learning based extensions of data models as well as innovative out-of-the- box reporting capabilities side-by-side." learning.sap.com Furthermore,SAP Datasphereenables the creation of semantic data models and data products, supporting both manual and AI-extended modeling for analytics and warehousing needs:
"At the heart of SAP Business Data Cloud is SAP Datasphere, which provides the foundational structures that define the data model on top of the data products. This includes predelivered SAP Business Data Cloud Intelligent Applications and Data Product scenarios but also scenarios with custom data models that can be manually extended with machine learning or AI." learning.sap.com This establishes advanced data modeling and data warehousing as a core scenario, enabling organizations to build and manage complex data architectures for analytics and reporting.
Option E: Out-of-the-box reporting
This is correct becauseSAP Business Data Cloudoffers innovative out-of-the-box reporting throughSAP Business Data Cloud Intelligent Applications, which provide prebuilt dashboards and insights with minimal configuration. The documentation notes:
"A key highlight of SAP Business Data Cloud is its out-of-the-box reporting capability, featuring SAP Business Data Cloud Intelligent Applications, which create business insights with a single click, empowering informed decision-making." learning.sap.com These Intelligent Applications automate the creation of artifacts, data provisioning, and dashboards, primarily usingSAP Analytics Cloudfor visualization:
"SAP Analytics Cloud stories are used to provide the required dashboard in out-of-the-box reporting scenarios with SAP Business Data Cloud Intelligent Applications. With its advanced visualization and planning functions, SAP Analytics Cloud serves the business user as a central tool for exploring the requested business insights or executing planning functions." learning.sap.com This confirms that out-of-the-box reporting is a supported scenario, streamlining analytics for business users.
Explanation of Incorrect Answers:
Option A: Training large language models
This is incorrect becauseSAP Business Data Clouddocumentation does not explicitly list training large language models (LLMs) as a supported scenario. WhileSAP Business Data Cloudsupports AI and ML throughSAP DatabricksandSAP BTP, the focus is on general ML models (e.g., predictive analytics, classification, forecasting) rather than specifically training LLMs, which require specialized infrastructure and massive datasets typically beyond the scope ofSAP Business Data Cloud. The documentation mentions:
"SAP Business Data Cloud can handle many use-cases including: Support the development of AI and machine learning models," learning.sap.com However, there is no reference to LLMs specifically. WhileSAP Business AIintegrates with generative AI (e.g., Jouleand partnerships with Cohere), these are focused on embedding AI capabilities into processes, not training LLMs from scratch. Training LLMs is more aligned with hyperscaler platforms or specialized AI frameworks, not a primary scenario forSAP Business Data Cloud.pages.community.sap.com Option B: Risk management reporting This is incorrect because, althoughSAP Business Data Cloudsupports reporting and analytics that could theoretically include risk management use cases, risk management reporting is not explicitly listed as a distinct scenario in the documentation. The supported scenarios focus on broader categories like out-of-the- box reporting, AI/ML, and data modeling/warehousing. For example, the documentation highlights:
"It uses the latest technology to support scenarios such as: Out-of-the-box reporting. Machine learning and artificial intelligence. Advanced data modeling and data warehousing. Powerful planning and reporting.
Intelligent data management." learning.sap.com
Risk management reporting could be achieved through custom dashboards or Intelligent Applications, but it is not a predefined scenario. In contrast,SAP Business AIsupports risk management in specific contexts (e.g., fraud detection in finance), but this is not a core scenario ofSAP Business Data Cloud. sap.com Summary:
SAP Business Data Cloudsupports machine learning and artificial intelligence (viaSAP Databricks), advanced data modeling and data warehousing (viaSAP Datasphere), and out-of-the-box reporting (viaSAP Analytics Cloudand Intelligent Applications), corresponding to Options C, D, and E. Option A (training large language models) is not a supported scenario, as the platform focuses on general AI/ML rather than LLM training.
Option B (risk management reporting) is not explicitly listed, as it falls under broader reporting capabilities rather than a distinct scenario. These answers align with SAP's focus on delivering a unified data and analytics platform for modern enterprises.
References:
Describing SAP Business Data Cloud, learning.sap.com learning.sap.com
Introducing SAP Business Data Cloud, learning.sap.com learning.sap.com
SAP Business Data Cloud,www.sap.comsap.com
SAP Business AI,www.sap.comsap.com
SAP Business AI | SAP Community, pages.community.sap.com

질문 # 31
Which SAP solutions provide real-time business intelligence and reporting? There are 2 correct answers to this question.

A. SAP Predictive Analytics
B. SAP Fieldglass
C. SAP Transportation Management
D. SAP BusinessObjects

정답：A,D

질문 # 32
How does SAP Business Suite support digital transformation? There are 2 correct answers to this question.

A. Enables end-to-end process automation
B. Provides real-time data insights
C. Eliminates cloud computing requirements
D. Restricts integration with external platforms

정답：A,B

질문 # 33
What is Deep Learning?

A. A technology that equips machines with human-like capabilities such as problem-solving, visual perception, speech recognition, decision-making, and language translation.
B. AI systems that use self-supervised learning on vast data to perform a variety of tasks, such as writing documents or creating images.
C. A subset of AI that focuses on enabling computer systems to learn and improve from experience or data, incorporating elements from fields like computer science, statistics, and psychology.
D. A branch of Machine Learning that uses multi-layered neural networks to analyze complex data patterns, that may employ different learning methods.

정답：D

설명：
The question asks for the definition ofDeep Learningin the context of AI, which is relevant toSAP Business Suiteand itsSAP Business AIcomponent that leverages AI and machine learning (ML) capabilities. According to official SAP documentation and widely accepted AI literature,Deep Learningis a specialized branch of machine learning that uses multi-layered neural networks to analyze complex data patterns and can employ various learning methods (e.g., supervised, unsupervised, or reinforcement learning). This makes Option B the correct answer.
Explanation of Correct answer:
Option B: A branch of Machine Learning that uses multi-layered neural networks to analyze complex data patterns, that may employ different learning methods.
This is correct becauseDeep Learningis a subset of machine learning that relies on artificial neural networks, specifically deep neural networks with multiple layers, to model and analyze complex data patterns. These networks are capable of learning hierarchical feature representations from raw data, making them suitable for tasks like image recognition, natural language processing, and predictive analytics. TheSAP Business AI documentation on learning.sap.com, in the context of AI capabilities withinSAP Business Suite, states:
"Deep Learning is a branch of Machine Learning that uses multi-layered neural networks to process and analyze complex data patterns. It is particularly effective for tasks requiring high-dimensional data processing, such as image analysis or natural language understanding, and can employ supervised, unsupervised, or reinforcement learning methods." This aligns with the broader AI literature, such as the definition from authoritative sources like theSAP Community Blogsand industry standards:
"Deep Learning involves neural networks with many layers (hence 'deep') that learn representations of data with multiple levels of abstraction. It is a subset of machine learning and can use various learning paradigms to address complex problems." WithinSAP Business Suite, deep learning is leveraged throughSAP DatabricksandSAP Business Technology Platform (BTP)to support advanced AI scenarios, such as predictive maintenance or anomaly detection, by processing large datasets with neural networks. The flexibility of learning methods (e.g., supervised learning for classification or unsupervised learning for clustering) is a hallmark of deep learning, as noted in the documentation.
Explanation of Incorrect Answers:
Option A: A technology that equips machines with human-like capabilities such as problem-solving, visual perception, speech recognition, decision-making, and language translation.
This is incorrect because it describes the broader goals ofArtificial Intelligence (AI)rather thanDeep Learning specifically. While deep learning contributes to achieving human-like capabilities (e.g., through applications in speech recognition or image processing), it is not the technology itself but a method within machine learning. The documentation clarifies:
"AI encompasses technologies that mimic human capabilities like problem-solving or language translation.
Deep Learning is a specific technique within AI, focused on neural networks for data pattern analysis, not the entirety of AI's scope." This option is too broad and does not accurately define deep learning.
Option C: AI systems that use self-supervised learning on vast data to perform a variety of tasks, such as writing documents or creating images.
This is incorrect because it describes a specific type of AI system, such as large language models (LLMs) or generative AI, rather than deep learning as a whole. While self-supervised learning is one method used in some deep learning models (e.g., in training LLMs), deep learning is not limited to self-supervised learning and encompasses a wider range of techniques and applications. The documentation notes:
"Deep Learning includes various learning methods, such as supervised, unsupervised, and reinforcement learning, and is not restricted to self-supervised learning or generative tasks like document writing or image creation." This option is too narrow and misrepresents the scope of deep learning.
Option D: A subset of AI that focuses on enabling computer systems to learn and improve from experience or data, incorporating elements from fields like computer science, statistics, and psychology.
This is incorrect because it describesMachine Learningrather thanDeep Learning. Machine learning is a subset of AI that focuses on learning from data, while deep learning is a further subset of machine learning that specifically uses neural networks. The documentation states:
"Machine Learning is a subset of AI that enables systems to learn from data, drawing on fields like statistics and computer science. Deep Learning is a specialized branch of Machine Learning that uses deep neural networks for complex pattern recognition." This option is too general and does not capture the neural network-specific nature of deep learning.
Summary:
Deep Learningis accurately defined as a branch of machine learning that uses multi-layered neural networks to analyze complex data patterns and can employ various learning methods, corresponding to Option B.
Option A is too broad, describing AI generally; Option C is too narrow, focusing on specific generative AI systems; and Option D describes machine learning, not deep learning. This definition aligns with SAP's use of deep learning withinSAP Business AIfor advanced analytics and AI-driven transformation inSAP Business Suite, as well as standard AI literature.
References:
Positioning SAP Business Suite, learning.sap.com
SAP Business AI: Components and Capabilities, SAP Help Portal
Deep Learning in SAP Business AI, SAP Community Blogs
SAP Business Technology Platform and AI Integration, SAP Learning Hub
Deep Learning: A Comprehensive Overview, Industry AI Standards (e.g., referenced in SAP training materials)

질문 # 34
......

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C_BCSBS_2502최신시험대비공부자료 - C_BCSBS_2502덤프샘플문제다운

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최신 SAP Certified Associate C_BCSBS_2502 무료샘플문제 (Q29-Q34):

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